• •• Teach graduate and undergraduate courses in Machine Learning, NLP, and Deep Learning (avg student eval: 4.7/5.0)
• •• Direct research laboratory of 5 PhD students, 2 MS students, and 8 undergraduate researchers
• •• Published 7 papers at premier conferences (NeurIPS, ACL, EMNLP, ICML) since appointment, with 300+ citations
• •• Secured $800K NSF CAREER Award for research on efficient language model architectures
• •• Serve on department admissions committee and undergraduate curriculum redesign task force

• •• Developed novel sparse attention mechanism reducing transformer inference cost by 40% without quality degradation
• •• Co-authored paper accepted at NeurIPS 2022 as spotlight presentation (top 5% acceptance rate)
• •• Collaborated with 3 senior research scientists on production deployment of efficient inference techniques
• •• Filed provisional patent for attention pattern pruning algorithm with improvements on 4 benchmark tasks

• •• Conducted doctoral research on efficient transformer architectures under Prof. Christopher Manning
• •• Published 8 papers during PhD including 3 first-author publications at ACL and EMNLP
• •• Taught CS224N (Natural Language Processing with Deep Learning) as head TA for 2 quarters (400+ students)
• •• Secured $200K DARPA grant for research on low-resource language understanding

Dissertation: "Efficient Transformers for Long-Context Understanding." Advisor: Prof. Christopher Manning.

GPA: 4.8/5.0. Tau Beta Pi. Undergraduate Research Opportunities Program (3 years). Valedictorian.